Importance sampling for polarization-mode dispersion

We describe the application of importance sampling to Monte-Carlo simulations of polarization-mode dispersion (PMD) in optical fibers. The method allows rare differential group delay (DGD) events to be simulated much more efficiently than with standard Monte-Carlo methods and, thus, it can be used to assess PMD-induced system outage probabilities at realistic bit-error rates. We demonstrate the technique by accurately calculating the tails of the DGD probability distribution with a relatively small number of Monte-Carlo trials.